Statistical analysis:
Statistical analysis included comparing different parameters between patients with pneumonia and COVID19 positive and those with COVID19 negative test results, using independent t-test for numerical variables and chi-square for categorical variables. All significantly different variables were entered in a forward stepwise binary logistic regression analysis to select the best model. After selecting the best model. The variable chosen in the last step was weighed using the odds ratios calculated from the regression coefficient (β) for each variable, the odds ratios were multiplied by 0.125 to calculate a score for each variable and the number was rounded to the nearest integer giving of scoring system of 10 points. All study group patients were scored. The cutoff point of the score was calculated using ROC analysis., and calculation of sensitivity, specificity and accuracy was performed. Also, variables associated with mortality in COVID19 positive were entered in a forward binary logistic regression, which selected the best model and the odds ratios was calculated for each variable using the regression coefficient (β). Before entering the variables in the regression analysis determination of the proper cutoff values of different contentious variables was done using ROC analysis. patients Data were entered checked and analyzed using SPSS for Windows version 16 (SPSS, Inc. Chicago, IL, USA). For all the above mentioned statistical tests, the threshold of significance is fixed at 5% level (P < 0.05).